| 引用本文: | 王晓卫,岳 阳,张 帆,等.基于注入扰动电流响应特征的主动式故障性质判别方法[J].电力系统保护与控制,2025,53(8):34-44.[点击复制] |
| WANG Xiaowei,YUE Yang,ZHANG Fan,et al.Active fault property discrimination method based on injected disturbance current response characteristics[J].Power System Protection and Control,2025,53(8):34-44[点击复制] |
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| 摘要: |
| 针对配电网相间短路后盲目重合于永久性故障导致系统遭受二次冲击，且保护跳开后自适应重合闸缺少可用有效信息的问题，提出一种利用外接电源注入扰动电流信号，通过其响应特征差异实现对故障性质可靠识别的方法。短路故障发生后，利用外接电源注入低频扰动电流，提取稳态扰动电压波形数据。若为瞬时性故障，线路间为电容模型。若为永久性故障，故障相间存在过渡电阻，线路不符合电容模型。故注入扰动信号在不同故障时响应特征存在明显差异，利用该差异构造判据。提出基于曼哈顿距离算法和能量相对熵算法表征的故障性质识别判据，并构造附加判据进一步识别永久性故障和注入信号时故障已消失的情况，克服主动式故障辨识方法应对故障随机性不足的问题。PSCAD/EMTDC仿真结果表明，所提方法具有较高的灵敏度和可靠性。 |
| 关键词: 配电网 注入法 能量相对熵 重合闸 相间故障 |
| DOI：10.19783/j.cnki.pspc.240927 |
| 投稿时间：2024-07-15修订日期：2024-11-12 |
| 基金项目:国家自然科学基金项目资助(52177114，61403127)；国网陕西省电力有限公司科技项目资助(5226KY23001U) |
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| Active fault property discrimination method based on injected disturbance current response characteristics |
| WANG Xiaowei1,YUE Yang1,ZHANG Fan1,WANG Yizhao2,ZHANG Zhihua2 |
| (1. School of Electrical Engineering, Xi’an University of Technology, Xi’an 710054, China;
2. State Grid Shaanxi Electric Power Research Institute, Xi’an 710199, China) |
| Abstract: |
| This paper proposes a method for reliably identifying fault nature by injecting disturbance current signals using an external power source, to address the issues of blind reclosing after inter-phase short circuits in distribution networks, which may lead to secondary impact on the system, and the lack of available effective information in adaptive reclosing after protection tripping. After a short circuit fault occurrence, an external power supply injects a low-frequency disturbance current and steady-state disturbance voltage waveform data are extracted. If it is a temporary fault, the inter-line relationship conforms to a capacitive model. If it is a permanent fault, the fault phases exhibit a transition resistance, deviating from the capacitance model. Therefore, the response characteristics of the injected disturbance signal differ significantly between different fault types, thus forming the identification criterion using the difference. This paper introduces a fault property identification criterion based on the Manhattan distance algorithm and the energy relative entropy algorithm. Additionally, an auxiliary criterion is established to further differentiate between permanent faults and cases where faults disappear during signal injection. This approach overcomes the limitations of active fault identification methods in handling fault randomness. PSCAD/EMTDC simulation results show the proposed method has high sensitivity and reliability. |
| Key words: distribution network injection method energy relative entropy reclosing inter-phase fault |
